Cortical Thickness Abnormalities at Different Stages of the Illness Course in Schizophrenia

Key Points Question Are there differences in cortical thickness (CTh) alterations between clinical high-risk (CHR), first episode of psychosis (FEP), and long-term illness stages of schizophrenia (SCZ)? Findings In meta-analyses comprising 2109 individuals across different illness stages of SCZ (10 studies of CHR, 12 studies of FEP, and 10 studies of long-term SCZ), CTh did not differ significantly between individuals with CHR and FEP, but those with long-term illness showed more pronounced CTh reductions than individuals with FEP. Accelerated age-related CTh reductions were found in frontotemporal cortex when combining all studies. Meaning The findings of this systematic review and meta-analysis do not indicate an emergence of CTh alterations with illness onset but suggest a progressively increasing thinning of CTh after illness onset.


eMethods 2. Quality assessment and data recording
A 12-parameter protocol was used to record average demographic and clinical characteristics of participants (sample size, gender, age, age of onset, illness duration, symptom severity, and medication status) and basic methodological information (statistical threshold of main findings and the method used to correct whole-brain results for multiple comparisons) (eTable 3). In the 12-point checklist 2 , each point was scored 1 as fully met, 0.5 as partially met, or 0 as unfulfilled, respectively. Any study scoring >6.0 was included in the present meta-analysis. The checklist was not designed to critique the investigators or the work itself, but to provide an objective indication of the rigor of the individual studies 2 . We also extracted the coordinates of significant findings and statistical values related to effect size (e.g. t statistics, Z score, or P value) for SDM calculations 3 .

eMethods 3. SDM method of meta-analysis
Meta-analyses of CTh abnormalities were conducted using SDM software (version 5.15). The details of the SDM method have been described elsewhere 4,5 , but we summarize the approach here. First, SDM uses the coordinates of cluster peaks and the effect sizes of significant differences between participants and controls to create an effect-size signed map for each study utilizing an anisotropic Gaussian kernel. When selecting coordinates, the same threshold was used throughout the whole brain in each study to avoid bias towards regions with liberal thresholds. Eligible studies that reported no group differences were also included and estimated conservatively to have a null effect size in SDM. We used the "VBM (voxelbased morphometry) -gray matter" modality, "gray matter" correlation template, and "FreeSurfer" mask to increase the accuracy of effect size maps, which restricted maps to cortical gray matter 6 . Next, SDM was used to perform a randomeffects analysis to obtain the mean map, combining data of each included study with both positive and negative differences included in the same map 4 . We used SDM's default thresholds (voxel threshold P<0.005 with peak Z>1 and a cluster extent of ten voxels) to display results in MNI coordinates.

eMethods 4. Jackknife, heterogeneity, and publication bias analysis
To test the replicability of results, whole-brain jackknife sensitivity analysis was conducted by repeating the main analysis N times (N=number of datasets in the meta-analysis), discarding one dataset at a time to determine whether the results remained significant 7 . Between-study heterogeneity was estimated using I 2 statistic. Publication bias was examined with Egger tests to assess the asymmetry of funnel plots for each significant cluster of patient-control comparisons, in which any result showing P<0.05 was judged to have significant publication bias 8 .

eMethods 5. Meta-regression analysis
Meta-regression analyses were performed in the combined sample. In secondary exploratory studies, similar analyses were conducted in each group separately. The effect size values of each cluster were extracted from the SDM software and used for regression analyses with clinical and demographic variables. Clinical variables were not included in metaregression analysis if data were available for fewer than nine studies 7 , and thus only one variable (i.e., age) was explored in the CHR group and two variables (i.e., age and illness duration) were explored in FEP group and long-term SCZ group. Six variables (i.e., age, onset age, illness duration, positive, negative, and general scores of Positive and Negative Syndrome Scale [PANSS]) were explored in the combined group. Notably, since CHR group had no illness duration, meta-regression of this variable was performed only using data from the FEP and long-term SCZ groups. Aging effects on the human brain are believed to follow a nonlinear trajectory even through midlife in some brain regions 9 , perhaps even more so in SCZ patients 10 . Thus, nonlinear (i.e., a quadratic model) regression models were further examined when testing for age relationships. Bonferroni adjustments corrected for the number of variables examined and the number of clusters. Therefore, the corrected P threshold for the CHR group, FEP group, long-term SCZ group, and the combined group was 0.05, 0.0083, 0.0063, and 0.0017 for linear regression analysis; and 0.05, 0.017, 0.0125, and 0.01 for nonlinear regression analysis of age, respectively. If both linear and quadratic models for age effects were significant for a cluster, performance of the two regression models was evaluated by their root-mean-square error (RMSE) (i.e., the standard deviation of the residual) with a leave-one-dataset-out cross-validation strategy, then RMSE values of the two models were compared using a paired Wilcoxon signed-rank test (P<0.05).

eResults. Detailed Results eResults 1. Results of quality assessments
The mean score of CHR studies was 9.7, 9.33 for FEP studies, and 9.95 for long-term SCZ studies (eTable 3). Quality assessment items that deducted the most scores of these studies were lack of desired information about medication status, comorbidity, coordinates availability, acquisition parameters, and subtype status.

eResults 2. Characteristics of studies included in the meta-analysis
Age did not differ between patients and controls in each included study, nor between studies in each of our three separate meta-analyses or in the pooled meta-analysis (all P>0.05). For FEP and long-term SCZ groups, there were no significant differences in sex ratio between patients and HCs in each included study (all P>0.05), nor in FEP (P=0.1702) or longterm SCZ (P=0.1156) meta-analyses. For the CHR group, three original studies showed significant between-group differences in sex ratio [11][12][13] , as did our meta-analysis of CHR studies (P<0.001). Three subdirectories of eTable 4 summarize the demographic and clinical characteristics of each included study for CHR, FEP, and long-term SCZ groups, respectively.

Characteristics of ten studies in CHR individuals
Among the ten included studies in CHR individuals, seven were cross-sectional and three were longitudinal. For these three longitudinal studies [14][15][16] , only baseline data were included. Two of the ten studies subdivided CHR samples into subgroups based on whether they converted to frank psychosis 14,15 and had psychotic symptoms 17 . Notably, different diagnostic criteria were used to define the CHR participants. Five studies used the Structured Interview for Prodromal Syndromes (SIPS) criteria 14,15,[17][18][19] , three used the Comprehensive Assessment of At-Risk Mental States (CAARMS) criteria 16,20,21 , one used Personal Assessment and Crisis Evaluation (PACE) criteria 11 , and the remaining one used the Early Detection and Intervention in Psychosis (TIPS) 22 .

Characteristics of 12 studies in individuals with FEP
Twelve studies were included in the FEP meta-analysis, in which eight were cross-sectional and four were longitudinally designed. Only baseline data of these four longitudinal studies were included 12,13,23,24 . FEP individuals of nine studies were medicated (less than a year) [11][12][13][24][25][26][27][28][29] , of two were medication-naive 30,31 , and one study recruited individuals with FEP who were at a wash-out period 23 . The illness duration of enrolled FEP individuals was specified in four studies 24,25,29,30 and unstated in two studies 11,13 . While other six studies described it as the duration of untreated psychosis since the treatment time was quite short (i.e., less than a year) 12,23,[26][27][28]31 . Among the 12 FEP studies, three studies divided FEP individuals into subgroups based on drug class 25 , cannabis use 24 , and medication status 30 , respectively. No significant case-control differences were reported in four of eight cross-sectional studies 26,28,30,31 , nor in all four longitudinal studies at baseline 12,13,23,24 . Thirteen datasets were eventually included in the present FEP meta-analysis.

Characteristics of ten studies in individuals with long-term SCZ
Ten included studies on CTh of long-term SCZ comprised nine cross-sectional and one longitudinal study. Only baseline data of the longitudinal studies were included 32 . Eight studies enrolled all medicated individuals, among which six studies reported chlorpromazine equivalent dosages with a mean daily dose of 531.68 mg [33][34][35][36][37][38] , one standardized the antipsychotic dosage using the defined daily dose with a mean unit of 1.53 39 , and the remaining one did not report the medication dosage 40 . One study recruited medication-naive individuals 10 , and the remaining one used a mixture of antipsychoticnaive patients and some with previously treated but currently untreated individuals 32 . Three studies recruited two subgroups depending on the treatment response 33,39 and homogeneous subtype 36 . Significant CTh differences were reported between long-term SCZ individuals and HCs in all included studies except the longitudinal study at baseline 32 . There were 12 datasets among the ten studies included in the final long-term SCZ meta-analysis.

Results of the CHR group
In the CHR group, whole-brain jackknife sensitivity analysis showed that decreased CTh in bilateral mPFC was preserved in 11 of 13 combinations (eTable 9). This region showed very low heterogeneity (I 2 =3.59%) between studies. Egger test of funnel plot asymmetry was not statistically significant (eFigure 8).

Results of the FEP group
In the FEP group, whole-brain jackknife sensitivity analysis showed that decreased CTh in the right lateral STC, ACC, and insula were preserved in 12, 11, and 13 of 13 combinations, respectively (eTable 10). The right lateral STC and ACC showed low heterogeneity (I 2 =5.92%, 11.17%, respectively) between studies, while the right insula showed high heterogeneity (I 2 =82.50%) between studies. Egger tests of funnel plot asymmetry were not statistically significant in the above three clusters (eFigure 9).

Results of the long-term SCZ group
In the long-term SCZ group, whole-brain jackknife sensitivity analysis showed that these CTh reductions were consistent, with effects in right insula and bilateral TP being preserved throughout all 12 combinations of datasets and those in the right pars orbitalis being significant in 11 combinations of 12 datasets (eTable 11). All findings showed low heterogeneity (I 2 =3.79%, 3.82%, 5.33%, and 8.4% for right insula, right pars orbitalis, left temporal pole, and right temporal pole, respectively) between studies. Egger tests of funnel plot asymmetry were not statistically significant in any of the above four clusters (eFigure 10).

Results of the combined group
In the combined group with 38 datasets in total, whole-brain jackknife sensitivity analysis showed that decreased CTh in the right insula, left ACC, right pars orbitalis of IFC, left lateral MTC, and right lateral MTC were preserved in 38, 36, 36, 33, and 38 combinations of 38 datasets, respectively (eTable 12). The left ACC, right pars orbitalis, left lateral MTC, and right lateral MTC showed low heterogeneity (I 2 =3.26%, 0.14%, 8.25%, and 15.16%, respectively) between studies, while the right insula showed moderate heterogeneity (I 2 =45.00%) between studies. The Egger tests of funnel plot asymmetry were not statistically significant in the above five clusters (eFigure 11). Long-term SCZ individuals showed decreased GMV in the thalamus, left uncus/amygdala region, the insula bilaterally, and the ACC than HCs. Abbreviations: CV, converters; NCV, nonconverters; CHR, clinical high-risk; SCZ, schizophrenia; VBM, voxel-based morphometry; GMV, gray matter volume; SBM, surface-based morphometry; CTh, cortical thickness; FEP, first-episode psychosis; AN-FEP, antipsychotic-naïve FEP; AT-FEP, antipsychotic-treated FEP; STC, superior temporal cortex; SFC, superior frontal cortex; ACC, anterior cingulate cortex; PFC, prefrontal cortex; IFC, inferior frontal cortex; PCC, posterior cingulate cortex; MTC, middle temporal cortex; ITC, inferior temporal cortex; MCC, middle cingulate cortex; vs, versus; HCs, healthy controls. eTable 2. The checklist of methodology quality assessment for the included studies 1. The checklist of methodology quality assessment for the included studies in CHR individuals* 12-point checklist 2 Bakker 18 Buechler 17 Cannon 14 Dukart 11 Gisselgård 22 Jung 20 Klauser 21 Kwak 19 Tognin 16 Ziermans 15 Category 1: Subjects 1 Patients were evaluated prospectively, specific diagnostic criteria were applied, and demographic data were reported The imaging technique used was clearly described so that it could be reproduced Total score 9.5 10.0 9.0 9.5 11.5 9.0 9.5 10.0 10.5 8.5 *Note: Each point was scored as 1, 0.5, or 0 if the criteria were fully met, partially met, or unfulfilled, respectively, and any study scoring >6.0 was included in the present meta-analysis.